{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         DATE  VALUE\n",
      "0  1948-01-01    3.4\n",
      "1  1948-02-01    3.8\n",
      "2  1948-03-01    4.0\n",
      "3  1948-04-01    3.9\n",
      "4  1948-05-01    3.5\n",
      "5  1948-06-01    3.6\n",
      "6  1948-07-01    3.6\n",
      "7  1948-08-01    3.9\n",
      "8  1948-09-01    3.8\n",
      "9  1948-10-01    3.7\n",
      "10 1948-11-01    3.8\n",
      "11 1948-12-01    4.0\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "unrate = pd.read_csv('unrate.csv')\n",
    "unrate['DATE'] = pd.to_datetime(unrate['DATE'])\n",
    "print(unrate.head(12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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TVV9c+7bXwLRvcryeHsDf0d6IvXdMzVbgZyzcfN3SbW9dVDPLxrn53GvNLNxP+Sbwhmmv\nZZl1zrBw/fgy/v/G5JWLaj5Ke2PyG932lbQ3n0+yMW4+91nzBV39h6a9jvVY76KaT7PBbz5PvYHX\n04OFa6sPAye651f/8xsAXx6p+0sWbkDOAX8x5jgbKRhWvWYW/iIr4EfAU93jI9Ne02us9c+An7Dw\nzZXbu7G7gA902+ex8I2UOeD7wDtGXnt797rjnKPfvJrkmoG/Af575HN9Ctg+7fWs5Wc8cowNHwz+\n8lmS1PBbSZKkhsEgSWoYDJKkhsEgSWoYDJKkhsEgSWoYDJKkhsEgSWr8L4G+I6VKUcyzAAAAAElF\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x5163d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.plot()# 画图\n",
    "plt.show()# 展现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RRKa02mQ28JSqZgMXAYtE5KiYRGS+iOSLSH55eXkgH+25/B37EYHPHRce/0lD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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x71a45d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "first_twelve = unrate[0:12]\n",
    "plt.plot(first_twelve['DATE'], first_twelve['VALUE'])# 折线图\n",
    "plt.xticks(rotation=45)# x轴标签倾斜\n",
    "plt.xlabel('Month')\n",
    "plt.ylabel('Unemployment Rate')\n",
    "plt.title('Monthly Unemployment Trends, 1948')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CJQgiIgqXIIiIKFyCICKicAmCKJakTZKOSpqSdO8s678k6YX69X1JP+9Zd7Zn3eRoex7R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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x81d58d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(2, 2, 1)\n",
    "ax1 = fig.add_subplot(2, 2, 2)\n",
    "ax1 = fig.add_subplot(2, 2, 4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x824b3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "fig = plt.figure(figsize=(3, 3))# 图形的大小\n",
    "ax1 = fig.add_subplot(2, 1, 1)\n",
    "ax2 = fig.add_subplot(2, 1, 2)\n",
    "\n",
    "ax1.plot(np.random.randint(1, 5, 5), np.arange(5))\n",
    "ax2.plot(np.arange(10)*3, np.arange(10))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AqyHWElfOuXOAO4ELvPe7grqflAxurFX6S6w1+lnpv/PCLkpidhOQ5ZxbDPQB\nxoVcT1yUvouYCSwClmDPz0gvD3fOPQf8A+jlnMt1zl0H3A+c6ZxbDpxZ+nHk1PDYHgXaAO+V5srj\ngdy3lryLiERLqra4RUQiS8EtIhIxCm4RkYhRcIuIRIyCW0QkYhTcIiIRo+AWEYmY/wX70jn29avo\nVAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x82d9b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "unrate['MONTH'] = unrate['DATE'].dt.month\n",
    "fig = plt.figure(figsize=(6, 3))\n",
    "\n",
    "plt.plot(unrate[0:12]['MONTH'], unrate[0:12]['VALUE'], c='red')\n",
    "plt.plot(unrate[12:24]['MONTH'], unrate[12:24]['VALUE'], c='blue')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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3797sfXv27KFdu3b4+fkRFRVFp06dcp2bnp7Ol19+yeOPP17s+vMjLVtCCCHK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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x92b3330>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 6))\n",
    "colors = ['red', 'blue', 'green', 'orange', 'black']\n",
    "for i in range(5):\n",
    "    start_index = i*12\n",
    "    end_index = (i+1)*12\n",
    "    subset = unrate[start_index:end_index]\n",
    "    label = str(1948+i)\n",
    "    plt.plot(subset['MONTH'], subset['VALUE'], c=colors[i], label=label)\n",
    "plt.legend(loc='best')# 定义标签位置\n",
    "plt.xlabel('Month, Integer')\n",
    "plt.ylabel('Unemployment Rate')\n",
    "plt.title('Monthly Unemployment Trends, 1948')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                             FILM  RT_user_norm  Metacritic_user_nom  \\\n",
      "0  Avengers: Age of Ultron (2015)           4.3                 3.55   \n",
      "1               Cinderella (2015)           4.0                 3.75   \n",
      "2                  Ant-Man (2015)           4.5                 4.05   \n",
      "3          Do You Believe? (2015)           4.2                 2.35   \n",
      "4   Hot Tub Time Machine 2 (2015)           1.4                 1.70   \n",
      "\n",
      "   IMDB_norm  Fandango_Ratingvalue  Fandango_Stars  \n",
      "0       3.90                   4.5             5.0  \n",
      "1       3.55                   4.5             5.0  \n",
      "2       3.90                   4.5             5.0  \n",
      "3       2.70                   4.5             5.0  \n",
      "4       2.55                   3.0             3.5  \n"
     ]
    }
   ],
   "source": [
    "reviews = pd.read_csv('fandango_scores.csv')\n",
    "cols = ['FILM', 'RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue', 'Fandango_Stars']\n",
    "norm_reviews = reviews[cols]\n",
    "print(norm_reviews.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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i5YlXqViZF7gDGB4RG0maFlgD+Dr5S31IRHxSfU/zUt1aJA0GfgUsERHLlee2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\nzKxD/D+tLQzxRfQKSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xee2390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 柱形图\n",
    "num_cols = ['RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue', 'Fandango_Stars']\n",
    "bar_heights = norm_reviews.loc[0, num_cols].values# 柱状图高度\n",
    "bar_positions = np.arange(5)# 柱状图位置\n",
    "tick_positions = range(0, 5)\n",
    "fig, ax = plt.subplots()\n",
    "# plt.bar(bar_positions, bar_heights, 0.3)# 0.3为柱宽\n",
    "\n",
    "ax.bar(bar_positions, bar_heights, 0.5)\n",
    "ax.set_xticks(tick_positions)\n",
    "ax.set_xticklabels(num_cols, rotation=45)\n",
    "\n",
    "ax.set_xlabel('Rating Source')\n",
    "ax.set_ylabel('Average Rating')\n",
    "ax.set_title('Average User Rating For Avebgers:Age of Ultron (2015)')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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7tyu+K+n/ka4fPwB8IreWK8ZLeg3oC5wbEVO7EMJhwNmSDiffJNaFOszMrMnU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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x81ffa50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 条形图\n",
    "bar_widths = norm_reviews.loc[0, num_cols].values\n",
    "bar_positions = np.arange(5)\n",
    "tick_positions = range(5)\n",
    "fig, ax = plt.subplots()\n",
    "ax.barh(bar_positions, bar_widths, 0.5)\n",
    "\n",
    "ax.set_yticks(tick_positions)\n",
    "ax.set_yticklabels(num_cols)\n",
    "ax.set_ylabel('Rating Source')\n",
    "ax.set_xlabel('Average Rating')\n",
    "ax.set_title('Average User Rating For Avebgers:Age of Ultron (2015)')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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32iaZLM1VaZtzPKrdrD93NBuQvjM1badv1gkK00ze5w5js/58p2BA+qvvtE0y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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf52650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 散点图\n",
    "fig, ax = plt.subplots()\n",
    "ax.scatter(norm_reviews['Fandango_Ratingvalue'], norm_reviews['RT_user_norm'])\n",
    "ax.set_xlabel('Fandango')\n",
    "ax.set_ylabel('Rotten Tomatoes')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                             FILM  RT_user_norm  Metacritic_user_nom  \\\n",
      "0  Avengers: Age of Ultron (2015)           4.3                 3.55   \n",
      "1               Cinderella (2015)           4.0                 3.75   \n",
      "2                  Ant-Man (2015)           4.5                 4.05   \n",
      "3          Do You Believe? (2015)           4.2                 2.35   \n",
      "4   Hot Tub Time Machine 2 (2015)           1.4                 1.70   \n",
      "\n",
      "   IMDB_norm  Fandango_Ratingvalue  \n",
      "0       3.90                   4.5  \n",
      "1       3.55                   4.5  \n",
      "2       3.90                   4.5  \n",
      "3       2.70                   4.5  \n",
      "4       2.55                   3.0  \n"
     ]
    }
   ],
   "source": [
    "reviews = pd.read_csv('fandango_scores.csv')\n",
    "cols = ['FILM', 'RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue']\n",
    "norm_reviews = reviews[cols]\n",
    "print(norm_reviews.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.7     2\n",
      "2.8     2\n",
      "2.9     5\n",
      "3.0     4\n",
      "3.1     3\n",
      "3.2     5\n",
      "3.3     4\n",
      "3.4     9\n",
      "3.5     9\n",
      "3.6     8\n",
      "3.7     9\n",
      "3.8     5\n",
      "3.9    12\n",
      "4.0     7\n",
      "4.1    16\n",
      "4.2    12\n",
      "4.3    11\n",
      "4.4     7\n",
      "4.5     9\n",
      "4.6     4\n",
      "4.8     3\n",
      "Name: Fandango_Ratingvalue, dtype: int64\n",
      "2.00     1\n",
      "2.10     1\n",
      "2.15     1\n",
      "2.20     1\n",
      "2.30     2\n",
      "2.45     2\n",
      "2.50     1\n",
      "2.55     1\n",
      "2.60     2\n",
      "2.70     4\n",
      "2.75     5\n",
      "2.80     2\n",
      "2.85     1\n",
      "2.90     1\n",
      "2.95     3\n",
      "3.00     2\n",
      "3.05     4\n",
      "3.10     1\n",
      "3.15     9\n",
      "3.20     6\n",
      "3.25     4\n",
      "3.30     9\n",
      "3.35     7\n",
      "3.40     1\n",
      "3.45     7\n",
      "3.50     4\n",
      "3.55     7\n",
      "3.60    10\n",
      "3.65     5\n",
      "3.70     8\n",
      "3.75     6\n",
      "3.80     3\n",
      "3.85     4\n",
      "3.90     9\n",
      "3.95     2\n",
      "4.00     1\n",
      "4.05     1\n",
      "4.10     4\n",
      "4.15     1\n",
      "4.20     2\n",
      "4.30     1\n",
      "Name: IMDB_norm, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "fandango_distribution = norm_reviews['Fandango_Ratingvalue'].value_counts()\n",
    "fandango_distribution = fandango_distribution.sort_index()\n",
    "\n",
    "imdb_distrbution = norm_reviews['IMDB_norm'].value_counts()\n",
    "imdb_distrbution = imdb_distrbution.sort_index()\n",
    "\n",
    "print(fandango_distribution)\n",
    "print(imdb_distrbution)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jy78Q3vK8U/6MdwNXjR7vZPmf5Y/e6rxTnvNHgJeMHv/kqNiy1Xl7zPPhwGnHPf5nYPeK\nMXtG8w7LOyufGjLDibaHvqokf5DkwtHTdwKPTnIv8GqgyW9KWjHnNwGPAP52dDpUc/fMWTHfk8KK\nOX8M+HqSe4AbgN+pqq9vXbrpWDHn1wAvTfJp4BqWy33bHj4FHgt8cjSfTwHXVdVHk7wsyctGYz4M\nfAG4F/gL4DeGDOCVopLUiG2xhy5JGs9Cl6RGWOiS1AgLXZIaYaFLUiMsdElqhIUuSY2w0CWpEf8H\nEspCArU+0gcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1071d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fix, ax = plt.subplots()\n",
    "# ax.hist(norm_reviews['Fandango_Ratingvalue'])\n",
    "# ax.hist(norm_reviews['Fandango_Ratingvalue'], bins=20)# 化为20个区间\n",
    "ax.hist(norm_reviews['Fandango_Ratingvalue'], range=(4, 5), bins=20)# 指定起始结束区间\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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JpIcknZy77yRpgaSl+f+OrS/XzKx+tbTwNgKnRsS+wMHAJyTtB8wGbomIKcAt+bmZWcca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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x916c990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 直方图\n",
    "fig = plt.figure(figsize=(5, 20))\n",
    "ax1 = fig.add_subplot(4, 1, 1)\n",
    "ax2 = fig.add_subplot(4, 1, 2)\n",
    "ax3 = fig.add_subplot(4, 1, 3)\n",
    "ax4 = fig.add_subplot(4, 1, 4)\n",
    "\n",
    "ax1.hist(norm_reviews['Fandango_Ratingvalue'], bins=20, range=(0, 5))\n",
    "ax1.set_title('Distribution of Fandango Ratings')\n",
    "ax1.set_ylim(0, 50)# 设置y轴区间\n",
    "\n",
    "ax2.hist(norm_reviews['RT_user_norm'], 20, range=(0, 5))\n",
    "ax2.set_title('Distribution of Rotten Tomatoes Ratings')\n",
    "ax2.set_ylim(0, 50)\n",
    "\n",
    "ax3.hist(norm_reviews['Metacritic_user_nom'], 20, range=(0, 5))\n",
    "ax3.set_title('Distribution of Rotten Metacritic Ratings')\n",
    "ax3.set_ylim(0, 50)\n",
    "\n",
    "ax4.hist(norm_reviews['IMDB_norm'], 20, range=(0, 50))\n",
    "ax4.set_title('Distribution of IMDB Ratings')\n",
    "ax4.set_ylim(0, 50)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAAD8CAYAAABXe05zAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x980c3d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 箱型图\n",
    "fig, ax = plt.subplots()\n",
    "ax.boxplot(norm_reviews['RT_user_norm'])\n",
    "ax.set_xticklabels(['Rotten Tomatoes'])\n",
    "ax.set_ylim(0, 5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sSB2qCk0c4/5XYHPqEDVynaReSS+RNLnvkTpUppZJOjV1iBrZJOl3KD9ZS3od8Ju0karR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\ny4yL28wsMy5uM7PM/H8I0mfnUR6u7wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x8c9b7d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_cols = ['RT_user_norm', 'Metacritic_user_nom', 'IMDB_norm', 'Fandango_Ratingvalue']\n",
    "fix, ax = plt.subplots()\n",
    "ax.boxplot(norm_reviews[num_cols].values)\n",
    "ax.set_xticklabels(num_cols, rotation=90)\n",
    "ax.set_ylim(0, 5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
